Exemple #1
0
def selectModel(args, m):
    model = None
    print("==> Creating model '{}'".format(m))
    if m.startswith(
            'senet'):  # block, n_size=1, num_classes=1, num_rgb=2, base=32
        model = nnmodels.senetXX_generic(args.num_classes, args.imgDim,
                                         args.base_factor)
        args.batch_size = 16
        args.batch_size = 16
        args.epochs = 85
        args.lr = 0.00005 * 2 * 2

    if m.startswith('densenet'):
        model = nnmodels.densnetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 75
        args.lr = 0.05
    if m.startswith('minidensenet'):
        model = nnmodels.minidensnetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 256
        args.batch_size = 256
        args.epochs = 76
        args.lr = 0.0005 * 2
    if m.startswith('vggnet'):
        model = nnmodels.vggnetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 256
        args.batch_size = 256
        args.epochs = 73
        args.lr = 0.0005
    if m.startswith('resnext'):
        model = nnmodels.resnetxtXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 56
    if m.startswith('lenet'):
        model = nnmodels.lenetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 56

    if m.startswith('wrn'):
        model = nnmodels.wrnXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 16
        args.batch_size = 16
        args.epochs = 56

    if m.startswith('simple'):
        model = nnmodels.simpleXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 100

    return model
def selectModel(args, m):
    model = None
    print("==> Creating model '{}'".format(m))
    if m.startswith(
            'senet'):  # block, n_size=1, num_classes=1, num_rgb=2, base=32
        # model = nnmodels.senetXX_generic(args.num_classes, args.imgDim, args.base_factor)
        model = nnmodels.senet32_RG_1_classes(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 56
        args.lr = 0.0005  # do not change !!! optimal for the Statoil data set

    if m.startswith('densenet'):
        model = nnmodels.densnetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 75
        args.lr = 0.05
    if m.startswith('minidensenet'):
        model = nnmodels.minidensnetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 32
        args.batch_size = 32
        args.epochs = 76
        args.lr = 0.0005 * 2
    if m.startswith('vggnet'):
        model = nnmodels.vggnetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 88
        args.lr = 0.0005
    if m.startswith('resnext'):
        model = nnmodels.resnetxtXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 16
        args.batch_size = 16
        args.epochs = 66
    if m.startswith('lenet'):
        model = nnmodels.lenetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 88

    if m.startswith('wrn'):
        model = nnmodels.wrnXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 16
        args.batch_size = 16
        args.epochs = 56

    if m.startswith('simple'):
        model = nnmodels.simpleXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 128
        args.batch_size = 128
        args.epochs = 120

    if m.startswith('unet'):
        model = nnmodels.unetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 50

    if m.startswith('link'):
        model = nnmodels.linknetXX_generic(args.num_classes, args.imgDim)
        args.batch_size = 64
        args.batch_size = 64
        args.epochs = 50

    return model